A Computational Approach to Scribal Practice

  • Ignacio Cases Martín Linguistics Department and Stanford NLP Group (Artificial Intelligence Lab), Stanford University
  • Alfonso Lacadena García-Gallo Departamento de Historia de América y Medieval y Ciencias Historiográficas. Universidad Complutense de Madrid
Keywords: scribal practice, computational sociolinguistics, Maya writing, natural language processing

Abstract

The study of the construction of social meaning in ancient Maya communities of Mesoamerica poses a variety of methodological problems in historical sociolinguistics due to the reliance on written records by means of a writing system that exhibits variation itself. While variation in writing systems has been previously studied in terms of diachronic shifts and dialectal variation, systematic approaches still remain elusive. This paper explores new avenues for the computational extraction of sociolinguistic features, resulting in the automatic extraction of useful sociolinguistic information from written corpora using Machine Learning algorithms. We show that these features can help illuminating the contribution of pragmatic choices in the selection of graphemes to stylistic practices that are key in the construction of Mayan scribal communities of practice.

Downloads

Download data is not yet available.
View citations

Article download

Crossmark

Metrics

Published
2019-07-05
How to Cite
Cases Martín I. y Lacadena García-Gallo A. (2019). A Computational Approach to Scribal Practice. Revista Española de Antropología Americana, 49(Especial), 209-224. https://doi.org/10.5209/reaa.64967